1,721,716 research outputs found
World Famous Scientist Lotfi A. Zadeh Azerbaijan "Era"
Get PDFOne of modern science's most important tasks is to research and examine the era, perspective and philosophical views of the genius scientist Lotfi A. Zadeh, who served science for 70 years and raised it "from earth to the universe" in the context of the historical philosophy. This article describes the "era" of Lotfi A. Zadeh, which started in Azerbaijan and ended with his eternity in Azerbaijan. This article is the part monograph of the Author of the article "Lotfi A. Zadeh. Of course, the main part of Lotfi A. Zadeh's "era" passed far away from Azerbaijan - to the United States. After a long break, in 1965, when he came to Russia for a conference, he made a short visit to Azerbaijan. The genius scientist's first and last live visit to Azerbaijan took place in 2008, which the Author of the article called this visit "21st century. The peak of Lotfi A. Zadeh Azerbaijan and Azerbaijanis "era". And the last - a genius scientist - returned to his native land once and for all when he died in 2017 at 96. This entire period is evaluated in the context of the philosophy of history in the article
Oral history interview with Lotfi A. Zadeh
No full textTranscript not available electronically. Please contact CBI.One of four interviews conducted in 1997 by Professor William Aspray concerning the history of the Purdue University Department of Computer Science.Zadeh, Lotfi Asker. (1997). Oral history interview with Lotfi A. Zadeh. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/107722
Fuzzy Logic and Soft Computing—Dedicated to the Centenary of the Birth of Lotfi A. Zadeh (1921–2017)
No full textIn 1965, Lotfi A. Zadeh published “Fuzzy Sets”, his pioneering and controversialpaper, which has now reached over 115,000 citations [...
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Reflections on some important contributions made by Lotfi A. Zadeh that have impacted my own research
No full textAbstractThis article provides very personal reflections on some of the important contributions made by Lotfi A. Zadeh that have made impacts upon my own research. Upon reflection, I found that his work-fuzzy and non-fuzzy-have influenced much of my career
Decomposition Methods for Adherence Problems in Finite Elasticity
No full textLe Tallec, P.; Lotfi, A.. (1987). Decomposition Methods for Adherence Problems in Finite Elasticity. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/4573
An integrated fuzzy logic system under Microsoft Azure using Simpful
No full textMobile applications in the area of human-centered applications are based on fuzzy logic have exhibited their effectiveness in managing intelligent environments, however the deployment of mobile fuzzy logic systems has been usually associated with dedicated hardware and software packages. Introducing openness for fuzzy logic systems offers exciting features such as system independence, simplicity, load balancing, and controlled resource allocation. On the other hand, while major cloud service providers support readymade commercial services for AI techniques such as for deep neural networks, there is no similar services for fuzzy logic systems. This study aims to develop a cloud-based fuzzy logic system under Microsoft Azure, employing Simpful as the cloud-side Python library and FML as data exchange standard. The developed cloud service is shown to effectively serve mobile phone applications for human monitoring purposes. Also in the present study, two types of fuzzy inference systems namely Mamdani and TSK have been utilized wherein both these systems have been compared on the basis of their processing time and accuracy of result. Results indicated that Mamdani fuzzy inference system outperformed TSK fuzzy inference system in terms of processing time by 0.456 seconds. Moreover, the detection accuracy of Mamdani system was found to be higher than that of TSK system by 6.82%
An Approximate Querying Environment for XML Data
No full textSeries on Studies in Fuzziness and Soft Computin
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